utilizing marginal net utility for recommendation …...utilizing marginal net utility for...

Utilizing Marginal Net Utility for Recommendation in

E-commerce Jian Wang & Yi Zhang

Informa(on Retrieval and Knowledge Management Lab University of California, Santa Cruz

1

• Will you like it? •  Tradi(onal recommender systems recommend item with the highest predicted ra(ng

2 Jian Wang & Yi Zhang Utilizing Marginal Net Utility for Recommendation in E-commerce

Recommenda(on based on Predicted Ra(ng is Not Good for Consumers

• Will you purchase it? •  Diminishing of return

•  A ra(onal user will purchase the product with the highest marginal net u(lity

Total Utility, Marginal Utility


Total U(lity

Marginal U(lity

Purchase Quan(ty



Total U(lity

Marginal U(lity

Purchase Quan(ty

Marginal Net Utility


Marginal Net Utility

= Marginal Utility - Price

1. Model the consumer behavior based on marginal net u6lity

2. Make recommenda6ons to maximize the marginal net u6lity for each user


Making Consumers Happier

Outline

• Mo(va(on •  Algorithm

–  Basic economics: two exis(ng u(lity func(ons studied by economists

–  Problem seOng

–  Propose a new u(lity func(on tailored for recommender systems

•  Experimental Results

•  Conclusion 9 Jian Wang & Yi Zhang Utilizing Marginal Net Utility for Recommendation in E-commerce

Basic Economics: Linear Utility Function

•  does not capture diminishing of return characteristic •  most existing algorithms are implicitly based on this utility function

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•  Total utility •  purchase history •  product ’s basic utility •  purchase quantity of product in •  marginal utility for the addition purchase of

Jian Wang & Yi Zhang Utilizing Marginal Net Utility for Recommendation in E-commerce

Basic Economics: Cobb-Douglas Utility

•  diminishing of return rate is fixed •  basic utility is not personalized



Making Consumers Happier: Recommendation based on Marginal Net Utility


Design • Design the u6lity func6onal form

Learn • Learn the u6lity func6on parameters from user history

Predict • Predict the marginal net u6lity of a product for a user using the func6on learned and user history

Rank • Rank products based on predicted marginal net u6lity

Problem SeOng


day 1 day 3 day 7 day 10

Time t

Design the U(lity Func(onal Form



Cobb-Douglas

New


Design the U(lity Func(onal Form

•  only same product will influence the marginal utility

New framework to revamp exis6ng recommenda6on algorithms

Revamp Exis(ng Algorithms

Marginal net utility


Take Singular Value Decomposition (SVD) as an example

Learn the U(lity Func(on Parameters

Maximum A Posteriori Estimation


Joint Likelihood

Purchase Likelihood Conditional on the marginal net utility

Outline



•  Conclusion


Experiment Dataset

•  More than 5-years purchase history from –  2004-01-01 to 2009-03-08

•  10,399 users, 65,551 products, and 102,915 unique (user, product) pairs

•  80% training, 10% validation, and 10% testing


Experiment Design

•  Methods to compare -  -  -  same product -  similar product

•  Evaluation Metric


General Analysis


0

0.02

0.04

0.06

0.08

0.1

0.12

0.14

0.16

1 2 3 4 5

Conversion

Rate

K

conversion rate@K

87.39%

Further Analysis

•  Consider all products –  13.79% repurchase –  90.64% new purchase

•  Evaluate orders with the specific purchase type (repurchase or new purchase)


Further Analysis

•  The new u(lity func(on achieves significantly beber performance in both tasks

•  Examples of Repurchases –  diaper, pet food, etc. –  Tend to be consumable products

•  Examples of New purchases –  computer, cell phone, bed frame, etc –  Tend to be durable product –  law of diminishing marginal u(lity


Outline



•  Conclusion


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Conclusion

Jian Wang & Yi Zhang Utilizing Marginal Net Utility for Recommendation in E-commerce

•  Introduce a new framework for recommender system in e-commerce sites

•  Recommend products with the highest marginal net utility

•  Take SVD as an example to revamp

•  Achieve significant improvement in the conversion rate

Utilizing Marginal Net Utility for Recommendation in

E-commerce Jian Wang & Yi Zhang

Informa(on Retrieval and Knowledge Management Lab University of California, Santa Cruz

26

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utilizing marginal net utility for recommendation …...utilizing marginal net utility for...

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